Triple
T15645950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cantina Traditional |
E376176
|
entity |
| Predicate | snackCourse |
P119590
|
FINISHED |
| Object | appetizer |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: appetizer | Statement: [Cantina Traditional, snackCourse, appetizer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: snackCourse Context triple: [Cantina Traditional, snackCourse, appetizer]
-
A.
courseCup
Indicates that a particular cup is used for or associated with serving a specific course in a meal.
-
B.
course
Indicates that an entity is an academic class or unit of instruction offered within an educational program.
-
C.
typicalCourse
Indicates that one entity is a standard or commonly taken course associated with another entity, such as a program, curriculum, or field of study.
-
D.
notableCourse
Indicates that a course is particularly significant, distinguished, or noteworthy in relation to an entity (such as a person or institution).
-
E.
courseIncludes
Indicates that a course contains or covers a particular component, such as a topic, module, lesson, or resource.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed5b8b081908d7127964eed3b09 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:15 a.m.